Many infrastructure systems such as water pipes and drainage systems require measurements of their operation on an ongoing basis. Sensors, of many kinds and types, are being deployed on site in order to measure various metrics and transmit the measurements, usually via a communication network, to a centralized control center, where the data is being analyzed. These sensors are usually energetically autonomous and are equipped with their own power source, which is usually in the form of a battery and therefore has a limited capacity.
Sampling the signal by the sensor and transmitting the data is power consuming and so the sampling scheme can significantly affect the power consumption of the sensors network as a whole. It is also known that some signals have a more predictable behavior in some time range and less predictable behavior in other time ranges.
WIPO Patent Publication number WO 2016/028365 teaches an apparatus for reducing sensor power consumption, in particular, through predictive data measurements by one or more sensors. In one instance, the apparatus may include one or more sensors and a sensor management module coupled with the sensors and configured to cause the sensors to initiate measurements of data indicative of a process in a first data measurement mode, determine a pattern of events comprising the process based on a portion of the measurements collected by the sensors in the first data measurement mode over a time period, and initiate measurements of the data by the one or more sensors in a second data measurement mode. The second data measurement mode may be based on the pattern of events comprising the process. The pattern may indicate a prediction of appearance of events in the process.
However, the aforementioned apparatus is limited for reducing power consumption of sensor where the signal to be sampled is periodic in nature and so is the prediction. Some signal are non-periodic but predictable all the same (a trivial example is a linear function). For these non-periodic signals, the aforementioned apparatus fail.
Therefore, it would be advantageous to provide a method to use knowledge of the predictability of the measured signal over time, in order to reduce the overall power consumption from the power sources upon which these sensors are dependent, irrespective of whether the signal to be sampled is periodic or not.